Space versus place in complex human–natural systems: Spatial and multi-level models of tropical land use and cover change (LUCC) in Guatemala

The relative role of space and place has long been debated in geography. Yet modeling efforts applied to coupled human–natural systems seemingly favor models assuming continuous spatial relationships. We examine the relative importance of place-based hierarchical versus spatial clustering influences in tropical land use/cover change (LUCC). Guatemala was chosen as our study site given its high rural population growth and deforestation in recent decades. We test predictors of 2009 forest cover and forest cover change from 2001 to 2009 across Guatemala's 331 municipalities and 22 departments using spatial and multi-level statistical models. Our results indicate the emergence of several socio-economic predictors of LUCC regardless of model choice. Hierarchical model results suggest that significant differences exist at the municipal and departmental levels but largely maintain the magnitude and direction of single-level model coefficient estimates. They are also intervention-relevant since policies tend to be applicable to distinct political units rather than to continuous space. Spatial models complement hierarchical approaches by indicating where and to what magnitude significant negative and positive clustering associations emerge. Appreciating the comparative advantages and limitations of spatial and nested models enhances a holistic approach to geographical analysis of tropical LUCC and human–environment interactions.

► We examine the importance of hierarchical versus spatial clustering models in LUCC.
► Geographically weighted regression and multi-level models were compared.
► Data for 2009 forest cover and 2001–2009 forest cover change in Guatemala were used.
► Models produced complementary results while highlighting important differences.
► The use and advantage of each model enhances a holistic approach to LUCC research.